1. Field of the Invention
This invention pertains generally to acoustic beamforming in an underwater array and more specifically a technique for use in shallow water wherein a post processor utilizing matched beam processing takes conventional beamforming outputs and determines a set of beam weighting coefficients that are applied to the conventional output, thereby producing a new set of beams for the accurate determination of an underwater objects bearing, range and depth.
2. Description of the Related Art
Signal processing in underwater acoustics has been centered around the problem of detection and localization of a target or signal in an ocean waveguide. Detection and localization of a quiet target requires the use of an array of hydrophones as the array processing gain will enhance the signal-to-noise (S/N) ratio of the target. Standard array processing assumes that the signal arrives as a plane wave. Conventional beamforming uses the concept of delay and sum of received plane wave signals to estimate the target bearing. With the advent of matched field/mode processing it is possible to extend the detection range by exploiting the multipath arrivals of low frequency signals using, for example, a large aperture vertical or horizontal array. Improved signal gain is obtained because a matched field processing matches the data with signal propagation in the waveguide. Matched field processing may also be used for source localization. The parameter estimation aspect of the method has been extensively investigated. Assuming that the acoustic environment of the ocean is known and the signal can be modeled for all source ranges and depth of interest, the bearing, range, and depth of the target is estimated by the highest correlation point in the correlation ambiguity function. If the correlation is in terms of the mode amplitudes of the replica and data field, one has a matched-mode processing.
For a horizontal line array or spherical array, conventional beamforming has been widely used for detection and bearing estimation of a target. In the target look direction, the signals are delayed and summed to yield the highest beam power. The highest beam yields the target bearing if the dominant arrivals of the signal are contained in one beam, as when the target look direction is near the broadside of the horizontal array. Conventional beamforming has worked successfully in deep water.
Shallow water is a complex environment for array processing because of the many surface and bottom bounced returns in the signal. Using conventional beamforming, the multipath arrivals can split the signal in several beams when the target is at a non-broadside direction and cause signal gain to be less than ideal, i.e., 20 log of the number of sensors. In a low loss environment, many bottom bounced returns will arrive at the array at relatively high grazing angles and result in severe bearing bias when the target is away from the roadside direction.; as when the arrival angle of a dominant bottom path differs from the target bearing. Also detection range can be substantially reduced due to signal gain degradation. This occurs when the incoming signal is split into several beams associated with the various multipath arrivals.
Matched field processing applied to a horizontal line array would, in principle, correct these deficiencies. When applied to the real world, several factors must be considered. First, in many shallow water environments the bottom bathymetry and bottom properties can change substantially over a short distance. The water column sound speeds may be site dependent and can change substantially over minutes, hours, and days due to inhomogeneous oceanographic processes taking place in shallow water. Source localization in shallow water can be sensitive to small changes in the bottom sound speed profile. This defines the mismatch problem. Secondly, the bearing of a target is estimated only when the target is properly localized in range and depth. This presents not only a heavy demand on the on-board processing power but also an incorrect bearing when the target is falsely localized. Lastly, the majority of techniques currently utilized are based on conventional beamforming.
With respect to bearing estimation and source localization, for a non-vertical array, matched field processing must search for bearing, range and depth simultaneously. For horizontal arrays, the conventional priority is to estimate the target bearing first. Several readings of bearing can be used to estimate target location by triangulation using either an array at several headings or multiple arrays. The bearing estimation is more robust than range, i.e., it is less sensitive to environmental mismatch. The arrival angle on a horizontal array can be estimated using conventional beamforming without the exact knowledge of the sound speed profile in the water column. Arrival angles can be used to calculate the target bearing if the arriving multipaths are known. This transformation is nominally done by a sonar operator with a calculator.
With respect to noise, matched field processing processes noise by localizing individual noise sources, e.g., ships or wind generated noise. Matched field processing requires a large bearing-range-depth volume to delineate the different noise sources and hence involves heavy computations. It requires a large three-dimensional array in order to have high resolution in bearing-depth-range. For practical arrays, the sidelobes associated with the many different noise sources contribute and raise the noise background at the target bearing-range-depth cell. Matched field processing applied to a vertical array covering the full water column in a shallow water environment has a limited ability to reject surface generated noise, i.e., noise gain can be higher than that of conventional beamforming.
Adaptive beamforming is a variation of conventional beamforming which has found many uses in real life problems such as interference nulling. Adaptive beamforming and adaptive beam weighting, or filtering, can be incorporated naturally into matched field processing in the frame work of matched beam processing. The conventional approach with respect to highly directional interfering noise sources is to use adaptive beamforming which steers a null in the direction of the interfering noise sources. This is a simple and effective method for noise rejection. The problem with conventional adaptive beamforming is that the signal energy is split over several beams which applies equally to the interfering noise sources.